Table REF  compares existing work on odometry estimation, in terms of their sensor type, model, whether a trajectory with an absolute scale is produced, and their performance evaluation on the KITTI dataset, where available. As deep inertial odometry has not been evaluated on the KITTI dataset, we do not include inertial odometry in this table. The KITTI dataset [1]} is a common benchmark for odometry estimation, consisting of a collection of sensor data from car-driving scenarios. As most data-driven approaches adopt the trajectory 09 and 10 of the KITTI dataset to evaluate model performance, we compared them according to the averaged Root Mean Square Error (RMSE) of the translation for all the subsequences of lengths (100, 200, .., 800) meters, which is provided by the official KITTI VO/SLAM evaluation metrics.
